Using Materials More Efficiently
The more calculations are automated and supported by AI, the more important the quality of the underlying material data becomes. This is because systems can process material properties quickly but cannot automatically determine whether they are truly suitable for a specific application.
Does the parameter match the temperature, size, and state?
At first glance, material properties may seem unremarkable in technical calculations. Yield strength, tensile strength, modulus of elasticity, and fatigue strength are selected, incorporated into the calculation, and subsequently form part of the verification. Yet this is precisely where the risk lies: A precise calculation can only be as reliable as the input data on which it is based.
This is because an existing design value is not automatically the correct one. What matters is the material condition to which it applies, the component dimensions that were taken into account, the temperature at which it may be applied, and the basis on which it was determined in the first place. Heat treatment and calculation methods can also influence which value is relevant for a specific design verification. Without this context, a number remains—but its technical significance becomes more difficult to assess.
This is something that’s easily overlooked in everyday practice, especially with familiar materials. A value has already been used multiple times, appears in an existing calculation, or is listed in a familiar table. As a result, it seems plausible at first glance. However, when dealing with a new geometry or changed operating conditions, this does not mean the value can simply be carried over unchanged.
The first critical point in a calculation can therefore arise before the first formula is even evaluated.
Material data becomes part of the digital chain of evidence
Today, technical data is increasingly rarely contained within a single program. It is passed between Design, calculation, simulation, Manufacture, quality assurance, and documentation, and reused in various process steps. This not only increases the volume of available data but also the need to describe it unambiguously and to correctly map it across system boundaries.
The world of standards illustrates just how important this issue has become. The ISO 8000-114:2024 addresses, among other things, semantic description, structured data formats, as well as metadata and reference data, to ensure that information remains unambiguously usable across systems. The ISO 8000 series thus views data quality not only as a matter of correct numerical values, but also as a matter of their unambiguous meaning and machine-readability.
In mechanical engineering, this is particularly relevant in what is known as the “digital thread.” NIST defines this as the end-to-end linking of information across various phases of the product lifecycle. Recent research shows that data from Design, planning, Manufacture , and quality must not only be collected, but also linked together so that traceability can actually be achieved. NIST: Spatial and Temporal Data Alignment for Digital Threads, 2024
This has a very practical implication for material data: A single property value is no longer sufficient. If it is no longer possible to determine later on what basis it was derived from, under what conditions it applies, and under what boundary conditions it was used, its continued use becomes a risk. A modern materials database must therefore not only provide data but also preserve the relationship between the material, the characteristic value, the boundary conditions, and the technical calculation.
Reduce manual transfers and additional invoices
This is precisely where the true value of a materials database in engineering is determined. It is not enough to uniquely identify a material and display a set of characteristic values for it. For the calculation, this information must be converted into a reliable input parameter. This requires that relevant influencing factors not have to be taken into account outside the database in additional tables or through separate auxiliary calculations.
In MDESIGN , material data is therefore directly linked to the respective calculation tasks. Depending on the application, parameters such as tensile strength, yield strength, yield point, elastic modulus, fatigue strengths, and temperature-dependent properties are available. For strength verifications, additional influencing factors such as effective diameter, component dimensions, and temperature can also be calculation. For FKM-based verifications, factors such as size and temperature effects, among others, are taken into account. The key factor here is not so much a single parameter as the end-to-end process from the material through the boundary conditions to the verification. MDESIGN Materials, Strengths, and Databases
This also changes the work of the design engineer. He no longer has to search multiple sources, transfer values, and then document where they came from. Material selection and calculation are brought together. The database thus becomes not merely a reference tool alongside the calculation, but an integral part of the calculation itself.
In " MDESIGN ," material information and boundary conditions relevant to the calculation can be directly linked. This not only reduces the need for manual data entry but also makes it clear which input variables form the basis for the subsequent analysis.
“What never ceases to surprise me is that companies invest a great deal of time in precise calculation models, yet when it comes to material properties, they sometimes still use values whose origin is barely documented. Yet it is precisely this input parameter that has a decisive impact on the result.”
Systematically Reuse Your Own Material Data
However, normative and published material data are only part of what companies actually use in their work. In addition, there are in-house test results, customer-specific materials, internally approved properties, and materials that—based on many years of experience—are evaluated differently than a general standard dataset.
This knowledge, in particular, is highly valuable because it comes directly from a company’s own products and development processes. Problems arise when such information is stored exclusively in individual project files or personal spreadsheets. In that case, for the next project, it’s not just a matter of finding the right material—it’s also necessary to first determine which version of a data set should be used at all.
MDESIGN It provides dedicated user databases for this purpose. Materials can be added using the integrated database functions and then used in the corresponding calculations. Centralized user databases on the network are also supported, provided the appropriate permissions are in place. This allows individual experience and knowledge to be transformed into a defined data foundation for future projects.
The difference is significant in everyday practice: Once a material has been qualified, it does not have to be reconstructed from old projects every time a new Design is created. Knowledge is not only stored but also becomes reusable.
And that's where AI comes in
At this point, at the very latest, the circle closes with regard to increasing automation in engineering. When systems automatically adopt parameter values, calculate variants, or support designers through AI assistants, the speed at which technical information can be processed increases. However, this also amplifies the impact of an inappropriate input value.
A calculation system can analyze a thousand variants using the same parameter. If this parameter has been incorrectly assigned for the specific use case, the result is not a thousand better results, but a thousand variants based on the same incorrect foundation. The quality of automated processes therefore depends directly on how unambiguously their technical input data is defined.
This makes structured material data a prerequisite for the effective use of AI in engineering. The more selection, transfer, and calculation are automated, the less the significance of a parameter should depend on the experiential knowledge of a single person. Automation saves work where the data foundation is unambiguous. Where it is not, automation primarily amplifies uncertainty.
MDESIGN studio demonstrates how corporate data and the knowledge of individual employees can already be leveraged for AI today.
MDESIGN Discover the StudioBe able to reliably trace calculations even years later
A second consequence often becomes apparent much later. During the initial Design , it is usually clear why a specific material and specific parameters were used. If the same calculation is reopened several years later, this context may already have been lost. In that case, a documented safety factor alone is not sufficient. For a reliable reassessment, it must remain clear which inputs were used, which boundary conditions applied, and on what computational basis the result was derived.
MDESIGN It therefore compiles input data, standards, boundary conditions, results, and graphs into technical calculation documentation. This means the documentation is not compiled retrospectively from various sources, but is generated directly from the calculation process itself.
This is particularly important when developing variants, sharing calculations internally, or explaining supporting documentation to customers and certification bodies. What seems obvious today must still be understandable in the future. A technically sound result is therefore not just one that has been calculated correctly; it must also be reproducible.
Reduce Development Time and Build Robust Solutions
This allows us to answer the article’s initial question more precisely. For industrial applications, their usefulness depends much more on what happens between the selection of a material and the final verification.
This is precisely where the strength of the MDESIGN approach lies: Material properties are incorporated directly into the calculation, while all modules follow the same user interface. Once learned, the workflow—from data entry to documentation—can be applied consistently across all modules.
Determine Your Own Material Properties Directly in " MDESIGN "
Try MDESIGN for 14 days, free of charge and with full access, using your own calculation examples. Select materials, take relevant boundary conditions into account, and see firsthand how property determination, calculation, and documentation work together in an end-to-end process.
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